PROJECT SUMMARY/ABSTRACT Over the past 30 years, a number of immunomodulatory agents have been tested in type 1 diabetes (T1D). While a handful of these trials met their primary endpoint, defined as an improvement in the C-peptide area under the curve response during a mixed meal tolerance test, no immunomodulatory intervention has yet proven capable of inducing insulin independence. Furthermore, no drug has been approved as a disease-modifying therapy for T1D, highlighting an important gap in translating T1D trial results into clinical practice. Here, we will test the hypothesis that targeted and model-based approaches to document early changes in ? cell function can refine current strategies aimed at preventing loss of insulin secretion in T1D. We have previously developed and validated a robust mathematical method to model dynamic parameters of ? cell function ? including ? cell glucose sensitivity, rate sensitivity, and potentiation ? and to estimate insulin sensitivity from standard oral glucose or mixed meal tolerance tests, known as the Mari/Ferrannini model. Here, we will apply the Mari/Ferrannini model to existing datasets from completed T1D intervention studies, performed in the Type 1 Diabetes TrialNet and the Immune Tolerance Networks, to define the natural history of ? cell decline in placebo-treated subjects (Aim 1) and determine whether short-term changes in sensitive model-derived parameters of insulin secretion and insulin clearance can be used to identify clinical and immunological Responders and Nonresponders at study end (Aim 2). The successful completion of this work will provide a framework for the design and execution of shorter trials, help dissect disease and trial heterogeneity, and provide rationale for targeting interventions to those with the highest prospect of benefit.